Structural implications of the DFD-in domain in computer-aided molecular design of MAP kinase interacting kinase 2 inhibitors.

Protein translation is a key process on cell development and proliferation that is often deregulated in cancer. MAP kinase interacting kinases 1 and 2(Mnk1/2) play a pivotal role in regulating the capdependent translation through phosphorylation ofeIF4E transcription factor. Thus, Mnk1/2 targeting have been proposed as a novel therapeutic strategy that would minimize side-effects in contrast to other therapies. For this reason, there is a growing interestin designing in silico new Mnk1/2 inhibitors which demands from reliable structural models. Interestingly,the catalytic domain of Mnk proteins are characterized by a DFD motif instead of the characteristicDFG motif of other kinases. However, Mnk2 structural models described in literature are DFG mutated and do not contain the activation loop. Molecular design techniques have been applied to obtain a structural model of the full wild type Mnk2 protein including the activation loop. The effect of the loop on the interaction mechanism of well-known ligands has been evaluated. Obtained results suggest that the presence of the activation loop is determinant for the correct prediction of the active site and it is essential for the design of new inhibitors

Lipoma of the Uterine Corpus: Exceptional Eventuality Combined with an Ovarian Thecoma

Uterine lipomas are very uncommon with symptoms that are similar to leiomyomas. Their diagnosis is always histological although some radiological methods may suggest their existence prior to surgery. They are sometimes associated with endometrial pathology, but there are no previous reported cases related to ovarian thecoma. Their prognosis is excellent. Clinical, radiological, morphologic, and immunohistochemical findings are shown which correspond to uterine lipoma associated with endometrial polyps and ovarian thecoma

Neuroglia at the crossroads of homoeostasis, metabolism and signalling: evolution of the concept

Ever since Rudolf Virchow in 1858 publicly announced his apprehension of neuroglia being a true connective substance, this concept has been evolving to encompass a heterogeneous population of cells with various forms and functions. We briefly compare the 19th–20th century perspectives on neuroglia with the up-to-date view of these cells as an integral, and possibly integrating, component of brain metabolism and signalling in heath and disease. We conclude that the unifying property of otherwise diverse functions of various neuroglial cell sub-types is to maintain brain homoeostasis at different levels, from whole organ to molecular

Model of Low-pass Filtering of Local Field Potentials in Brain Tissue

Local field potentials (LFPs) are routinely measured experimentally in brain tissue, and exhibit strong low-pass frequency filtering properties, with high frequencies (such as action potentials) being visible only at very short distances ($\approx$10~$\mu m$) from the recording electrode. Understanding this filtering is crucial to relate LFP signals with neuronal activity, but not much is known about the exact mechanisms underlying this low-pass filtering. In this paper, we investigate a possible biophysical mechanism for the low-pass filtering properties of LFPs. We investigate the propagation of electric fields and its frequency dependence close to the current source, i.e. at length scales in the order of average interneuronal distance. We take into account the presence of a high density of cellular membranes around current sources, such as glial cells. By considering them as passive cells, we show that under the influence of the electric source field, they respond by polarisation, i.e., creation of an induced field. Because of the finite velocity of ionic charge movement, this polarization will not be instantaneous. Consequently, the induced electric field will be frequency-dependent, and much reduced for high frequencies. Our model establishes that with respect to frequency attenuation properties, this situation is analogous to an equivalent RC-circuit, or better a system of coupled RC-circuits. We present a number of numerical simulations of induced electric field for biologically realistic values of parameters, and show this frequency filtering effect as well as the attenuation of extracellular potentials with distance. We suggest that induced electric fields in passive cells surrounding neurons is the physical origin of frequency filtering properties of LFPs.Comment: 10 figs, revised tex file and revised fig

Role of transport performance on neuron cell morphology

The compartmental model is a basic tool for studying signal propagation in neurons, and, if the model parameters are adequately defined, it can also be of help in the study of electrical or fluid transport. Here we show that the input resistance, in different networks which simulate the passive properties of neurons, is the result of an interplay between the relevant conductances, morphology and size. These results suggest that neurons must grow in such a way that facilitates the current flow. We propose that power consumption is an important factor by which neurons attain their final morphological appearance.Comment: 9 pages with 3 figures, submitted to Neuroscience Letter

Neuron-glia crosstalk in health and disease: fractalkine and CX3CR1 take centre stage

An essential aspect of normal brain function is the bidirectional interaction and communication between neurons and neighbouring glial cells. To this end, the brain has evolved ligand–receptor partnerships that facilitate crosstalk between different cell types. The chemokine, fractalkine (FKN), is expressed on neuronal cells, and its receptor, CX(3)CR1, is predominantly expressed on microglia. This review focuses on several important functional roles for FKN/CX(3)CR1 in both health and disease of the central nervous system. It has been posited that FKN is involved in microglial infiltration of the brain during development. Microglia, in turn, are implicated in the developmental synaptic pruning that occurs during brain maturation. The abundance of FKN on mature hippocampal neurons suggests a homeostatic non-inflammatory role in mechanisms of learning and memory. There is substantial evidence describing a role for FKN in hippocampal synaptic plasticity. FKN, on the one hand, appears to prevent excess microglial activation in the absence of injury while promoting activation of microglia and astrocytes during inflammatory episodes. Thus, FKN appears to be neuroprotective in some settings, whereas it contributes to neuronal damage in others. Many progressive neuroinflammatory disorders that are associated with increased microglial activation, such as Alzheimer's disease, show disruption of the FKN/CX(3)CR1 communication system. Thus, targeting CX(3)CR1 receptor hyperactivation with specific antagonists in such neuroinflammatory conditions may eventually lead to novel neurotherapeutics

Enhancing neural-network performance via assortativity

The performance of attractor neural networks has been shown to depend crucially on the heterogeneity of the underlying topology. We take this analysis a step further by examining the effect of degree-degree correlations -- or assortativity -- on neural-network behavior. We make use of a method recently put forward for studying correlated networks and dynamics thereon, both analytically and computationally, which is independent of how the topology may have evolved. We show how the robustness to noise is greatly enhanced in assortative (positively correlated) neural networks, especially if it is the hub neurons that store the information.Comment: 9 pages, 7 figure

Update of the recommendations for the determination of biomarkers in colorectal carcinoma: National Consensus of the Spanish Society of Medical Oncology and the Spanish Society of Pathology

In this update of the consensus of the Spanish Society of Medical Oncology (Sociedad Española de Oncología Médica SEOM) and the Spanish Society of Pathology (Sociedad Española de Anatomía Patológica SEAP), advances in the analysis of biomarkers in advanced colorectal cancer (CRC) as well as susceptibility markers of hereditary CRC and molecular biomarkers of localized CRC are reviewed. Recently published information on the essential determination of KRAS, NRAS and BRAF mutations and the convenience of determining the amplifcation of human epidermal growth factor receptor 2 (HER2), the expression of proteins in the DNA repair pathway and the study of NTRK fusions are also evaluated. From the pathological point of view, the importance of analysing the tumour budding and poorly diferentiated clusters, and its prognostic value in CRC is reviewed, as well as the impact of molecular lymph node analysis on lymph node staging in CRC. The incorporation of pan-genomic technologies, such as next-generation sequencing (NGS) and liquid biopsy in the clinical management of patients with CRC is also outlined. All these aspects are developed in this guide, which, like the previous one, will remain open to any necessary revision in the future

Beyond Hebb: Exclusive-OR and Biological Learning

A learning algorithm for multilayer neural networks based on biologically plausible mechanisms is studied. Motivated by findings in experimental neurobiology, we consider synaptic averaging in the induction of plasticity changes, which happen on a slower time scale than firing dynamics. This mechanism is shown to enable learning of the exclusive-OR (XOR) problem without the aid of error back-propagation, as well as to increase robustness of learning in the presence of noise.Comment: 4 pages RevTeX, 2 figures PostScript, revised versio

Five microRNAs in Serum Are Able to Differentiate Breast Cancer Patients From Healthy Individuals

Breast cancer is the cancer with the most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients vs. 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based on the expression levels of five microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the overexpression and downregulation of proteins differently expressed in the serum of breast cancer patients vs. that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue, and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a, miR-497, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of miR-125b, miR-29c, miR-16, miR-1260, and miR-451 was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of miR-16 with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and the potential use of the predictor here described are discussed